Saturating controller design of UAVs based on Markovian jump model

The unmanned aerial vehicles (UAVs) are wildly used in many fields for their excellent performance, such as the process of emergency, information acquisition and disaster relief. This paper investigates controller design for UAVs suffering from noise disturbance and input saturation, in which Markovian jump model is proposed to model such dynamic process. Since the stochastic noise is non-guassian, a new algorithm named particle control is applied to ensure the reliability and security of the UAVs. Considering huge complexity of the algorithm resulting from particle number and time length, we introduce a simplified algorithm which greatly reduces the complexity and improves the real-time performance while ensuring the reliability. The simulation results show the effectiveness of this algorithm.